helpResearch questionMedical AI Trust, Clinical Decision Support, and Patient-Provider Collaboration
What factors drive patients toward more conservative choices such as accepting biopsy under conflicting AI and doctor recommendations?AI Explainability, Trust, and Calibration / Medical AI Trust, Clinical Decision Support, and Patient-Provider Collaboration
What factors drive patients toward more conservative choices such as accepting biopsy under conflicting AI and doctor recommendations?
Similar questions
helpResearch questionMedical AI Trust, Clinical Decision Support, and Patient-Provider Collaboration
How can explainable AI (XAI) methods for medical diagnosis be designed to align with domain knowledge systems and reasoning processes?helpResearch questionMedical AI Trust, Clinical Decision Support, and Patient-Provider Collaboration
How do diagrammatic explanations and selective abductive reasoning improve AI explanation credibility and user trust in cardiac diagnosis?helpResearch questionMedical AI Trust, Clinical Decision Support, and Patient-Provider Collaboration
How does the DiagramNet model simultaneously improve predictive performance and explainability in heart sound diagnosis?helpResearch questionMedical AI Trust, Clinical Decision Support, and Patient-Provider Collaboration
How do AI conversational agents using encouraging language affect users' self-efficacy in performing health self-checks?helpResearch questionMedical AI Trust, Clinical Decision Support, and Patient-Provider Collaboration
Can encouraging language from such AI agents improve trust in the agent, especially the benevolence dimension?helpResearch questionMedical AI Trust, Clinical Decision Support, and Patient-Provider Collaboration
Which feedback type—encouraging or neutral language—is more effective in health self-check tasks?Related papers
CHI 2025
Diagrammatization and Abduction to Improve AI Interpretability With Domain-Aligned Explanations for Medical Diagnosis
Brian Y Lim, Joseph Paul Cahaly, Yu Feng Chester Sng
CHI 2025
Enhancing Self-Efficacy in Health Self-Examination through Conversational Agent's Encouragement
Naja Kathrine Kollerup, Maria-Theresa Bahodi, Samuel Rhys Cox
CHI 2025
Understanding Attitudes and Trust of Generative AI Chatbots for Social Anxiety Support
Yimeng Wang, Yinzhou Wang, Kelly Crace
CHI 2025
Architecting Utopias: How AI in Healthcare Envisions Societal Ideals and Human Flourishing
Catherine Wieczorek, Heidi Biggs, Kamala Payyapilly Thiruvenkatanathan
CHI 2025
Who is Trusted for a Second Opinion? Comparing Collective Advice from a Medical AI and Physicians in Biopsy Decisions After Mammography Screening
Henrik Detjen, Lars Densky, Niklas von Kalckreuth
CHI 2025
MedAI-SciTS: Enhancing Interdisciplinary Collaboration between AI Researchers and Medical Experts
Chen Cao, Yu Wu, Xiao Zoe Fang
CHI 2025
Selective Trust: Understanding Human-AI Partnerships in Personal Health Decision-Making Process
Sterre van Arum, Hüseyin Uğur Genç, Dennis Reidsma
CHI 2025
Accurate Insights, Trustworthy Interactions: Designing a Collaborative AI-Human Multi-Agent System with Knowledge Graph for Diagnosis Prediction
Haoran Li, Xiaoping Zhang, Xusen Cheng
CHI 2024
Explorable Explainable AI: Improving AI Understanding for Community Health Workers in India
Ian René Solano-Kamaiko, Dibyendu Mishra, Nicola Dell
CHI 2024
How Much Decision Power Should (A)I Have?: Investigating Patients’ Preferences Towards AI Autonomy in Healthcare Decision Making
Dajung Kim, Niko Vegt, Valentijn Visch
CHI 2024
Patient Perspectives on AI-Driven Predictions of Schizophrenia Relapses: Understanding Concerns and Opportunities for Self-Care and Treatment
Dong Whi Yoo, Hayoung Woo, Viet Cuong Nguyen
CHI 2024
Sketching AI Concepts with Capabilities and Examples: AI Innovation in the Intensive Care Unit
Nur Yildirim, Susanna Zlotnikov, Deniz Sayar